Expeed Software

We are in the era where your digital capabilities, in addition to being excellent at your core product or service, are going to make or break your business. The customer journey towards buying your product or service first starts digitally. It is important that you provide an utterly smooth experience to customers along their journey towards your products/services, as well as after purchasing your products/services. To note, we should further define what we mean by customer to expand the definition past those that are paying fees. Today’s customers include your employees.

Employees expect the same smooth experience as they interact with every part of your organization’s software applications. Organizations that find themselves using outdated software, disconnected systems that keeps data in silos and prevents business analysis degrade your organization’s ability to not only compete in the marketplace, but also compete for talent. It doesn’t matter how big and established your business is, today’s capabilities and affordability of technologies are enabling even start-ups to threaten you in a short span of time. Any business that hasn’t recognized the importance of Digital Innovation is at the danger of losing their marketshare.

Once you understand the importance of Digital Innovation and decided to take action, it is important to have clear goals for your Digital Innovation. You need to decide what your goals are to achieve the expected results. There are three kinds of opportunities with Digital Transformation or Digital Innovation:

Business Operation Efficiency

Transform Your Operations

Evolve Your Business Model or Redevelop Your Business Model

To start down the path of Digital Innovation, here are a few tips to ensure success:

– Create a cross functional team of people with passion for driving change. No matter which area of the business they come from, common traits they will have are keen ability observe current practices, identify shortcomings in the current practices, have ideas to either to transform current practices or establish totally new ones.

-Get buy in from each of the functionals areas to get either part of their time or full time to participate in innovation activities

-Embrace agile and DevOp methodologies to quickly see ideas in action. Be quick to prototype and iterate as necessary and to not hesitate to toss out an idea if that doesn’t seem like viable one

-Experiment with UX/UI paradigms and emerging technologies and frameworks such as Angular, React, Function as a service concepts, scalable databases NoSQL and NewSQL databases such as CosmosDB, Google Spanner, and CockroachDB

-Look beyond your current or available packaged solutions and COTS applications as they may not be the solution for this kind of innovation. You want to have a team capable of quickly developing and iterating custom applications as necessary. If you don’t have those development skills, find a noble and reliable development partner, like Expeed Software, who can get you off the ground and into rhythm quickly.

To be sure, the promised benefits of Digital Innovation are huge, but it does take a solid strategic plan, a detailed plan of execution and an organizational culture that supports change.

If you Google the term “marketing automation” or run in certain crowds, you are well familiar what insiders call “MA”; however, many organizations are just now at the point of learning what marketing automation is all about and how it differs from traditional tools. To be sure, there is a bit of marketing snobbery at play and the trendsetters at organizations have long had marketing automation in their tech stack (whether they’re truly using it as marketing automation and not just mass email is an entirely different matter altogether). Don’t feel bad if your organization is just getting to the point of trying to discern the differences between marketing automation and traditional tools such as website, email and search engine marketing.

We believe that moving to marketing automation tools is a definite step in the digital transformation journey and it’s important that we meet organizations where they are in order to shepherd them through at a pace that creates sustainable results. To understand marketing automation and what it can do for you, consider five reasons why organizations adopt marketing automation platforms over an ecosystem of point tools such as web, email, surveys and digital advertising. These distinctions are the major reasons that organizations move to marketing automation:

The Need to Automatically MeasureIf each software tool that a marketer uses has metrics, then trying to amass a comprehensive dashboard to track a customer’s journey will involve going into each software tool, pulling metrics and trying to fit them together. This is not a big deal if you’re using, let’s say, just two pieces of software such as your website and email marketing. The problem is that marketers don’t just use two pieces of software anymore, do we? We typically are using 8-15 different tools and trying to get a beat on a dashboard is a monumental task. Marketing automation platforms hit the scene nearly ten years ago and are only now hitting mass adoption because it’s become clear that digital is the most cost effective and easiest to measure, but we need easier ways to measure. Marketing automation platforms bundle together a variety of tools and automatically connect them so that the pulling together of metrics is done for you. Your job can shift from the time-intensive process of pulling together metrics to actually analyzing the metrics to make good decisions.

One Campaign, Multiple Channels

Another top reason that organizations move to marketing automation is that one campaign no longer consists of one email send. With the adoption of integrated marketing campaigns, marketers are bundling multiple channels of communication into one campaign effort and want to be able to measure the outcome at both the aggregate level, as well as per channel level. I might want to bring a new product to market and advertise it through Google AdWords, Facebook, Instagram, a roadside billboard and a radio ad. All of these channels are being used to promote my product with different amounts of money being spent on each and I want to know which channel works the best, as well as my overall effect of all of my channel spend for the campaign. Did the overall campaign generate the awareness or leads that I sought? I need one platform that can tie these channels together and manage the measurement for me.

One Customer, Multiple Pathways

Continuing our example, each prospective customer or customer does not exist in a bubble. This one prospect may see my ad in search, drive by my billboard while hearing my radio ad (wouldn’t that be ideal??). With adult attention span now less than 4 seconds, marketers must rely on layering messages to first get the attention of humans in hopes of getting the message to stick. We need to understand the buyer journey so that we can get the right messages in front of the buyer to sway them our way and need one tool to manage these pathways. Marketing automation becomes the platform that allows us to do create, manage and measure the multiple pathways of a customer’s journey in interacting with our messaging.

Behavioral SegmentationWhen planning out where to place messaging, it would be far more effective to rely on data that evidences the actual moves a buyer has made rather than guessing. If I want to send an email and get in front of people that are thinking about my product, wouldn’t it make sense to be able to pull together a list of all people who were just on my product webpage in the last two days or interacted with my Twitter feed in the last week, or a combo of both? Being able to add in actual digital behaviors of users in conjunction with demographic and psychographic data is a key reason for moving to marketing automation.

Cost Per LeadThere’s no CFO out there that doesn’t want to fully understand where every penny of the organization’s money goes. Marketers need hard, not fuzzy, math in being able to explain where marketing funds were spent and what return they got. Marketing automation solves this problem by bundling together the budget and responses in one platform to provide you with the cost per lead which makes it very clear where to spend each new penny!

The second half of the Women in Analytics Conference continued with break-out sessions and networking opportunities. As the attendees settled in for the rest of the day, three common points were heard across all of the discussions:

finding a purple unicorn that possesses all the skills needed in data science is improbable; therefore, you need to look to assemble a team

the educational discipline in which you studied is often irrelevant, what is relevant is curiosity and the ability to collaborate

data science/analytics team are often repurposed from other roles and responsibilities and nascent teams need to put together a new identity and look for quick wins to shore up their legitimacy as a new organizational entity to prevent individuals from getting pulled into traditional work

Many of the sessions in the afternoon and the keynote during dinner focused on starting, building and keeping teams together. Sandy Steiger discussed the importance of focusing on re-investing in staff so that they stick with the company. With data scientists and analysts in such high demand, she pointed out that it’s hard enough to attract talent, but keeping talent is a wholly different endeavor.

One of the most interesting things to emerge with bringing so many different types of organizations and roles together is that we were able to network and find out how different companies had structured teams and in which department they resided. The common theme in this conversation is that the data analytics or science team(s) are often odd ducks sitting in a traditional IT department, but marketing has not yet made the leap to see how they should do more than liaise with the team. Many data professionals felt that they were an island unto themselves and it poses the question if we’re not seeing the org chart about to get disrupted with the data teams becoming the center of a hub-and-spoke organizational model because they are closest to the customer.

The implications of data science and the adoption of AI and machine learning are so vast that the conference ended with the invitation to get more involved in the community. It’s clear that this conference and working group is here to stay and Columbus will be the host city for a tremendous number of meeting of the data minds from here on out.

A sold out crowd for this year’s Women in Analytics Conference provided quick evidence of what an exciting time we’re experiencing. The attendee base encompasses a wide variety of titles, job roles, company sizes and educational backgrounds giving further credence to the cross-functional nature of the profession.

Robin Davies, Director of Data Operations, Global Data Insights & Analytics for Ford Motor Company started the day with explaining how Ford is using an analytics-first approach to rethink their customer journey. The insights coming from their analytics are helping the organization rethink not only product roll-out strategy, but also pricing strategies. One example given was that if they can understand their customer better to view them from a more lifecycle approach, then this can be fed back into their pricing model to offer lower price points to entry with increased confidence as to the total lifetime customer value. Davies also spent time explaining the enormity of data and how much data is really there to harness with all of us still really being at the very beginning of the process.

From the sessions we attended in which each speaker surveyed the room to understand the breakdown between developers, data scientists, analysts and functional business roles, there was a pretty even spread across the board. One session, in particular, hit the bulls eye in terms of cross-cutting techniques and applications and that was on word embedding. Bijaya Zenchenko of HomeAway blew everyone away with word embedding and the many different techniques and approaches readily available. We walked away wondering why are organizations still spending so much time manually trying to understand the digital customer journey and not pouring their money into an application that can scrape, aggregate and accelerate insights?

The lunchtime panel provided different viewpoints from women in analytics working in academia, functional leadership role and data engineering to hear first individually their work in the analytics’ field. Each presentation was unique with the common theme being that analytics is a commitment and defining it is paramount to achieving any sort of success. The caution towards understanding data bias came up repeatedly and each speaker was in agreement that we will not be overtaken by bots anytime in the near future. The panelists additionally agreed that the culture of an organization is a make-it-or-break-it element to analytics adoption and appreciation.

The upcoming Women in Analytics Conference that will be held on March 15th at the Columbus Convention Center is the talk of many Slack channels and Twitter feeds. As an initiative of the Tech Community Coalition, the event is expected to be exponentially larger than previous years due to the growing commitment to make Columbus the data analytics capital of the country.

Expeed Software is proud to send two of our staff to support the analytics movement and support growing the number of women practicing advanced analytics and data science. With key speakers from top firms in Columbus, the sessions cover a wide range of artificial intelligence, machine learning and security topics. Additionally, the conference includes sessions on career pathways and ample opportunities to network with like-minded people.

Plan on following @expeedsoftware on Twitter this Thursday for our live tweet coverage of the event with an in-depth synopsis following the event.

Day one of the Gartner Data & Analytics Summit was packed with sessions and vendors of all sizes who are offering software products to help data scientists do less programming and more analysis. The consistent theme of the first day of the conference came down to three key takeaways:

Key Takeaway #1: Advanced Data Analytics is Just Getting Going
While there is a ton of buzz about the promise of advanced data analytics, the analysts were consistent in their assessment that the industry is still in its infancy. One key stat that stuck out was that it’s estimated that 70% of the work involved in applying machine learning algorithms revolves around data preparation. A new class of software applications called Augmented Analytics is coming to market with the aim to automate data preparation to speed up the process of analysis. As any data scientist will tell you, the biggest hurdle to analysis is getting the data prepped in a way that creates a complete set so that you can then slice and dice as you see fit. Companies like DataRobot, ClearStory Data and Paxata are bringing new tools to market to help automate the messy stage of data prep that everyone likes to gloss over, but is the key to good data science.

Key Takeaway #2: Artificial Intelligence is Accelerating in Adoption
Gartner cited that 10 years ago AI was known as a sci-fi movie (and even old then), but that in the last 10 years, AI is starting to crop up everywhere. With more and more availability of AI, it is being plugged into applications to help accelerate product adoption, product longevity, increase safety and more. In fact, once you start thinking from the digital transformation viewpoint which centers on the customer, it’s hard not to start brimming with ideas for where AI could add value in either obtaining needed information from the consumer to allow the product to perform better or sending information that would be useful to help the consumer perform better. This two-way communication between entity-to-consumer holds so many possibilities that product innovation is anticipated to exponentially soar as devices and applications get re-wired from an AI framework.

Key Takeaway #3: Innovate or Consolidate
With the need for agile development and time to market being critical elements of market success, the pressure for companies to innovate is intense. The market share of the usual giants of IBM, Microsoft and Oracle are under constant attack from smaller competitors that are faster to market with innovative new products. With such disruption in the marketplace, Gartner anticipates that there will be a wave of new start-ups, but that consolidation is inevitable and larger conglomerates will emerge.

You might have heard the term predictive analytics and thought “that’s what I’ve always wanted”!!! For most marketers, this is the case and you blame the IT group for not being able to provide the dashboard and reports to show you what you know the data is trying to tell you. While true marketers have a highly attuned sense of intuition and insight, better outcomes will also result when we don’t skip steps. Here’s five ways to get started down the path of predictive analytics that will help you work better with your IT team and bring about long-term results:

1) Minimze What You Want to MeasureWhaaaaa???? I finally have all this data and you’re telling me to minimize what I want? (Please note that I did not say simplify, but minimize–big diff). Many marketers drive business analysts and IT personnel crazy by wanting to have everything on a dashboard or available to query because of FONHI (fear of not having it). This is inherent in marketers and makes many of us equivalent to data hoarders who are scared that we might not be able to undertake the segmentation that we want at the exact moment that we want it. While painful, listen to your IT partners and focus on what it is that you really need to measure that will drive the business forward.

2) Get the Right Data
You don’t need all the data, but you do need the key data as we’ve previously stated. The likelihood that all key data is in the same database is next to nil; moving to an enterprise architecture where it doesn’t matter where the physical location of the data lives is key. Organizations will increasingly need to move to modern data architecture models that focus on tying systems together making the movement and aggregation of data the primary concern and not the database architecture.

3) Prepare Data for a Predictive Analytics Model
Data can only be properly analyzed when it can be joined and segmented in multiple different ways. You need to ensure that your data is clean, proper data hygiene practices are followed and that it is structured in such a way that you can easily access it, move it and measure it.

4) Putting Processes in Place for Using a Predictive Analytics Model
Ensuring that staff understand the importance of capturing and cleaning data for use in analytics is key. Reviewing all entry points of data across the customer lifecycle from the viewpoint of analytics is a useful exercise to identify all of the areas where data is incomplete, erratic, overly restrictive and identifying processes that cause friction to the user can help showcase which processes are in need for an overhaul.

5) Use the Right Tools
Predictive analytics is typically a new endeavor for organizations and requires different technology products and methodologies to maximize success. Ensuring that your organization has a strong technology partner that has the expertise to consult on both the business and technology fronts will allow your organization to expedite its digital transformation. While the right tools are a necessity, the know how is the critical element in the world of predictive analytics.

Google dubbed it the “Zero Moment of Truth” to explain that point at which you realize that the customer, not you, is completely in control. Perhaps we were fooling ourselves all along to think that we did have control of our ordering process, inventory, distribution, customer service and accounting and the truth is we never really did. Alternatively, we could surmise that we lost total control the day that mass penetration of mobile occurred and consumers started doing their own research on our brands–without our involvement.

Regardless of when this ZMOT occurred at your company, we can all agree that nothing will ever be the same. Consumer attention spans are inversely correlated to the product options now available online for purchase. In fact, studies now cite that consumers have an attention span of less than 4 seconds which is below that of a goldfish. What’s worse is that consumers are finicky and will typically spend even less than 4 seconds on your website once they have arrived there from an enticing ad or other promotional hook. The consumer has a seemingly unlimited number of possible products, the power of information and moreso, the power to inform others about their own experiences.

This new reality means that corporations must now shift their viewpoint from one of being internally striving to push products out to a distant market to one that begins and ends with the customer. The movement of shifting one’s entire worldview along with the associated business processes and technological infrastructure is what is typically referred to as digital transformation.

Now that the customer is self-empowered through the ability to find information and product reviews online, the need to understand the customer is at an all-time high. We need to be able to study the customer’s every digital move and take action at the exact right time in order to gain our next sale. We need to understand what the customer is telling us through digital so that we can provide similar products and services that match their online sentiment. This need to not only capture, but predict, what the consumer may do next is at the cross-roads of customer experience and digital.

Given this lens, the intersection of customer experience (CX) and digital is far easier to understand because it breaks down to simple economics. My organization needs as much information as possible about consumers so that we may take the right action at the right time to supply the right product. Digital is the fastest, most measurable, most economical way and typically, preferred channel for consumers to research and make purchases. My conclusion becomes that my organization needs to overhaul our thinking about the customer journey and leverage digital to gain insight.

When you get to this conclusion and you are ready to start taking action to understand how your organization needs to look to support a digital and customer-first operational model, it’s time to contact Expeed.

We, here at Expeed, are focused on helping our clients understand the importance of Digital Transformation and how it is relevant to their businesses. Depending on the size and industry of your business, you could be at different levels of understanding or maturity on the Digital Transformation curve. Some of the Fortune 500 organizations understand the importance of this initiative and have been actively putting organizational structures in place to pursue their true potential with Digital Transformation, while a lot of organizations are either not paying attention to it or confused about all the noise in the industry. No matter where you are in the journey, we are committed to working with our clients as a trusted partner to make the journey as smooth as possible.

Digital Transformation is a multi-pronged approach; it needs understanding of where you are in your business, identify the opportunities with digital transformation, set goals, create a roadmap, and create teams that can deliver digital products in an agile manner. Your products need to improve the experience of customers as well as your employees. The key theme of your new products should be focused on providing an integrated experience–asking users to switch between multiple applications to achieve something is a thing of past. When it comes to your data analytics, it is imperative that it is not a siloed application available to only a few people. Analytics need to be part of the regular work flow of your employees and customers.

Again, we here at Expeed are committed to helping our clients in this journey. To deepen our understanding of the role of Data Analytics in Digital Transformations, and how different organizations and industries are approaching this initiative, I am attending Gartner’s Data Analytics Summit next week (March 5 to 8th) in Grapevine, Texas. Throughout the conference, I will be looking for answers such as:

where do certain industries fall and is it correlated to size of business on the Digital Transformation continuum

what are the opportunities available– especially for midsize businesses that exist

what are the risks for businesses if they do not embrace these trends that could enable even startups to challenge existing business modelsI will try to summarize my findings when I return from the event.